Abstract
Accuracy and computational complexity are challenges of stereo matching algorithm. Much research has been devoted to stereo matching based on cost volume filtering of matching costs. Local stereo matching based guided image filtering (GIF) has a computational complexity of O(N). A proposed algorithm focuses on reduction of computational complexity using the concept of fast guided image filter, which increase the speed up to O(N=s2) with a sub-sampling ratio s. Experi- mental results using the Middlebury benchmark indicated the proposed algorithm achieved effective local stereo matching with a fast execution time.
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